Confidence intervals for the regression coefficient in a simple regression model with a balanced two-fold nested error structure. Issue 17 (1st September 2016)
- Record Type:
- Journal Article
- Title:
- Confidence intervals for the regression coefficient in a simple regression model with a balanced two-fold nested error structure. Issue 17 (1st September 2016)
- Main Title:
- Confidence intervals for the regression coefficient in a simple regression model with a balanced two-fold nested error structure
- Authors:
- Park, Dong Joon
Yoon, Min - Abstract:
- ABSTRACT: In applications using a simple regression model with a balanced two-fold nested error structure, interest focuses on inferences concerning the regression coefficient. This article derives exact and approximate confidence intervals on the regression coefficient in the simple regression model with a balanced two-fold nested error structure. Eleven methods are considered for constructing the confidence intervals on the regression coefficient. Computer simulation is performed to compare the proposed confidence intervals. Recommendations are suggested for selecting an appropriate method.
- Is Part Of:
- Communications in statistics. Volume 45:Issue 17(2016)
- Journal:
- Communications in statistics
- Issue:
- Volume 45:Issue 17(2016)
- Issue Display:
- Volume 45, Issue 17 (2016)
- Year:
- 2016
- Volume:
- 45
- Issue:
- 17
- Issue Sort Value:
- 2016-0045-0017-0000
- Page Start:
- 5053
- Page End:
- 5065
- Publication Date:
- 2016-09-01
- Subjects:
- Inference -- Mixed model -- Regression coefficient
62J05 -- 62F25
Mathematical statistics -- Periodicals
Mathematics
Statistics
519.2 - Journal URLs:
- http://www.tandfonline.com/ ↗
- DOI:
- 10.1080/03610926.2014.935435 ↗
- Languages:
- English
- ISSNs:
- 0361-0926
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3363.432000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 1282.xml